Pretargeted Multimodal Tumor Imaging by Enzymatic Self-Immobilization Labeling and Bioorthogonal Reaction

Yinxing Miao1, Yuqi Wang1, Yefeng Chen2

  • 1State Key Laboratory of Analytical Chemistry for Life Science, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Road, Nanjing 210023, China.

Insights

Researchers developed E-SIM, a new method for rapid and selective cancer cell membrane labeling. This enzyme-triggered strategy improves in vivo tumor imaging and therapy by attaching bioorthogonal handles for precise reporter enrichment.

Area of Science:

  • Bioconjugation Chemistry
  • Molecular Imaging
  • Cancer Therapeutics

Background:

  • Covalent cell membrane modification shows potential for tumor imaging and therapy.
  • Current methods suffer from slow kinetics, poor cancer cell selectivity, off-target effects, and suboptimal in vivo efficacy.

Purpose of the Study:

  • To develop a rapid and selective tumor cell membrane labeling strategy for in vivo applications.
  • To enable pretargeted multimodality imaging and therapy by enriching bioorthogonal reporters on cancer cells.

Main Methods:

  • Introduced E-SIM (Enzyme-triggered Self-Immobilization), utilizing an alkaline phosphatase (ALP)-responsive quinone methide (QM) precursor (P-TCO) with a trans-cyclooctene (TCO) group.
  • Employed proximity labeling for rapid, high-density conjugation of TCO handles onto tumor cell membranes in vivo.
  • Utilized fast bioorthogonal reaction between TCO handles and tetrazine (Tz)-bearing reporters for reporter enrichment.

Main Results:

  • Demonstrated E-SIM enables rapid and selective labeling of tumor cell membranes with TCO handles in vivo.
  • Achieved efficient enrichment of various sized Tz-bearing reporters on labeled tumor cell membranes.
  • Successfully applied E-SIM for pretargeted bioluminescence imaging of liver tumor metastases using Tz-modified Renilla luciferase, enabling sensitive detection and surgical guidance.

Conclusions:

  • E-SIM is a robust strategy for precise in vivo tumor cell labeling in complex biological environments.
  • The approach facilitates pretargeted enrichment of diverse reporters for multimodal tumor imaging and therapeutic applications.
  • E-SIM enhances in vivo imaging sensitivity and accuracy, offering potential for improved cancer detection and treatment guidance.